8 research outputs found
Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets
Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology
Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets
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136235.pdf (publisher's version ) (Open Access)Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology
Prognostic impact of gross tumor volume during radical radiochemotherapy of locally advanced non-small cell lung cancer-results from the NCT03055715 multicenter cohort study of the Young DEGRO Trial Group (Jan, 10.1007/s00066-020-01727-4, 2021)
Background In radical radiochemotherapy (RCT) of inoperable non-small-cell lung cancer (NSCLC) typical prognostic factors include T- and N-stage, while there are still conflicting data on the prognostic relevance of gross tumor volume (GTV) and particularly its changes during RCT. The NCT03055715 study of the Young DEGRO working group of the German Society of Radiation Oncology (DEGRO) evaluated the prognostic impact of GTV and its changes during RCT. Methods A total of 21 university centers for radiation oncology from five different European countries (Germany, Switzerland, Spain, Belgium, and Austria) participated in the study which evaluated n = 347 patients with confirmed (biopsy) inoperable NSCLC in UICC stage III A/B who received radical curative-intent RCT between 2010 and 2013. Patient and disease data were collected anonymously via electronic case report forms and entered into the multi-institutional RadPlanBio platform for central data analysis. GTV before RCT (initial planning CT, GTV1) and at 40-50 Gy (re-planning CT for radiation boost, GTV2) was delineated. Absolute GTV before/during RCT and relative GTV changes were correlated with overall survival as the primary endpoint. Hazard ratios (HR) of survival analysis were estimated by means of adjusted Cox regression models. Results GTV1 was found to have a mean of 154.4 ml (95%CI: 1.5-877) and GTV2 of 106.2 ml (95% CI: 0.5-589.5), resulting in an estimated reduction of 48.2 ml (p 0.05). In patients with available data on both GTV1 and GTV2, absolute GTV1 before RT was not significantly associated with survival (HR 0-69, 0.32-1.49, p > 0.05) but GTV2 significantly predicted OS in a model adjusted for age, T stage, and chemotherapy, with an HR of 3.7 (1.01-13.53, p = 0.04) per 300 ml. The absolute decrease from GTV1 to GTV2 was correlated to survival, where every decrease by 50 ml reduced the HR by 0.8 (CI 0.64-0.99, p = 0.04). There was no evidence for a survival effect of the relative change between GTV1 and GTV2. Conclusion Our results indicate that independently of T stage, the re-planning GTV during RCT is a significant and superior survival predictor compared to baseline GTV before RT. Patients with a high absolute (rather than relative) change in GTV during RT show a superior survival outcome after RCT